The relative contributions of the X chromosome and autosomes to local adaptation

Abstract

Models of sex chromosome and autosome evolution yield key predictions about the genomic basis of adaptive divergence, and such models have been important in guiding empirical research in comparative genomics and studies of speciation.

In addition to the adaptive differentiation that occurs between species over time, selection also favors genetic divergence across geographic space, with subpopulations of single species evolving conspicuous differences in traits involved in adaptation to local environmental conditions. The potential contribution of sex chromosomes (the X or Z) to local adaptation remains unclear, as we currently lack theory that directly links spatial variation in selection to local adaptation of X-linked and autosomal genes.

Here, we develop population genetic models that explicitly consider the effects of genetic dominance, effective population size, and sex-specific migration and selection, on the relative contributions of X-linked and autosomal genes to local adaptation.

We show that X-linked genes should nearly always disproportionately contribute to local adaptation in the presence of gene flow. We also show that considerations of dominance and effective population size — which play pivotal roles in the theory of faster-X adaptation between species — have surprisingly little influence on the relative contribution of the X chromosome to local adaptation. Instead, sex-biased migration is the primary mediator of the strength of spatial large-X effects.

Our results yield novel predictions about the role of sex chromosomes in local adaptation. We outline empirical approaches in evolutionary quantitative genetics and genomics that could build upon this new theory.

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The focus of my research is on understanding the genetic basis of adaptation to environmental change.

My group uses a range of approaches that include comparisons of populations collected from along latitudinal gradients, experimental evolution, quantitative genetics, phenotypic manipulations and genomics... MORE